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The WelCOM project aims to bring in new methods, tools and services to facilitate the implementation of a Condition – Based Maintenance Strategy (CBM), employing a flexible toolset of solutions based on Wireless Sensor Networks and Mobile Devices. Thus, maintenance – related data and services become ubiquitously and transparently available anytime, anywhere and to anyone with authorised access. This constitutes the key concept of e-Maintenance.

The WelCOM platform is designed to have the flexibility to adapt and operate on top of diverse plant installations and equipment profiles.

 

WelCOM Overview

The main technical objectives of this project are:

  1. A wireless network platform of sensor devices providing the infrastructure for on-line and on-spot measuring (muli-sensors), processing (CPU powered modules) and acting (hardware actuators, switches and software reporting services).
  2. An innovative and versatile optical sensor, ported in both wired and wireless form, which can be used for diverse monitoring applications, ranging from industrial machinery condition monitoring, to structural integrity monitoring of infrastructures.
  3. A set of software tools and services that provide maintenance technicians and engineers with advanced means of local (PDA, mobile) and remote (web, intranet):
    • access to machinery condition state data, alarms and reports
    • access to intelligent advisory services that support decision making and preventive maintenance programs.
    • have advanced but practical multi-user interfaces, including speech interfaces, enabling fast and efficient human-computer device interaction to be implemented on-site and remotely.
    • calibration of the monitoring infrastructure and configuration of its operational parameters,
    • scheduling and management of maintenance activities and their supporting procedures.
  4. Development of small-scale sensor embedded intelligence to :
    • capture - condition monitoring feeds of sampled parameters reflecting the operating behaviour,
    • detect – identify deviations from known/expected operating state
    • diagnose – identify operating conditions and faults.
    • predict – offer prognostic functions, such as remaining life estimations
 

This project is financed by the Greek Secretariat for Research & Technology through project
No: 09SYN-71-856, NSRF 2007-2013.